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Biology, Bioinformatics, Computer Science, or a related field • Strong programming skills in R and/or Python • Experience with analysis of single-cell sequencing data • Familiarity with spatial
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and technicians to solve analytical challenges and develop, optimize, validate and apply analytical methods to evaluate food safety. Key Responsibilities - Perform trace-level analysis of organic
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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for decarbonization strategies o Fluency in task automation, data cleaning and analysis in a programming language, with a preference for Python and/or R o Strong organizational skills and exceptional attention
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collection and analysis. There will be scope to contribute to the design of visual or interactive outputs (such as infographics or dashboards) and shape the development of a future larger-scale cohort study
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are welcome. Skills are not essential but experiences in the following areas are preferred: biological physics, quantitative biology, nonlinear dynamics, stochastic simulations, dynamic systems, numeric
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nuclear and particle-physics experiments Experience with data analysis and knowledge of statistical techniques for data analysis Experience with computing and software for high-energy or nuclear physics
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analysis), and one or more of: CRISPR, microfluidics, next-generation sequencing experiments, or developing diagnostic technologies. Proficient in scientific writing. History of academic productivity and
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with numerical modeling codes such as ASPECT or Underworld Geodynamics (UWG). Preferred Qualifications: Familiarity with landscape evolution modeling tools like Fastscape or BADLANDS is highly desirable
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability